Personal authentication apparatus and personal authentication method

ABSTRACT

A personal authentication apparatus including a facial region extraction which extracts an image of a facial region of a person obtained from image sensing input unit, a guide unit which guides motion of the person of interest, a feature amount extraction unit which extracts the feature amount of a face from the image of the facial region extracted by the facial region extraction unit while the motion is guided by the guide unit, a dictionary registration unit which registers the feature amount extracted by the feature amount extraction unit as a feature amount of the person of interest, and an authentication unit which authenticates the person of interest in accordance with the similarity between the feature amount extracted by the feature amount extraction unit, and a feature amount which is registered by the dictionary registration unit.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation Application of, and claims thebenefit of priority under 35 U.S.C. § 120 from, U.S. application Ser.No. 10/462,620, filed Jun. 17, 2003, which claims the benefit ofpriority under 35 U.S.C. § 119 from Japanese Patent Application No.2002-282443, filed Sep. 27, 2002. The entire contents of each of theabove applications are incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a personal authentication apparatus andpersonal authentication method, which can implement registration and apersonal authentication method with high reproducibility.

2. Description of the Related Art

In recent years, interests and demands about the security technique aregrowing. There are some personal authentication methods that assuresecurity. In a personal authentication system that uses a magnetic cardsuch as a credit card or the like, or a contact type IC card with abuilt-in IC chip, a user must insert such card into a reader. When theuser has his or her hands full with some pieces of baggage, theoperation for inserting the card into the reader is troublesome and veryinconvenient. In a personal authentication system that uses anon-contact type IC card represented by a commuter pass ticketexamination system using a wireless communication, the user need notmanually insert the card into a reader unlike the system that uses thecontact type IC card. However, if the user loses his or her card, suchcard may be illicitly used as in the contact type. Also, the user mustalways carry the IC card.

By contrast, a personal authentication system that uses biometricinformation (biometrics) such as a fingerprint, iris, voice, face, andthe like is known. In this system, the iris pattern of the user isregistered in an authentication apparatus in advance, and is verifiedupon authentication. This authentication system can assureauthentication precision 10 times as high as fingerprints. However, inorder to assure high authentication precision, the eye must beirradiated with auxiliary light, and the user must bring his or her faceinto contact with an authentication apparatus. Hence, the system forcesthe user to take given authentication actions, and cannot assure user'shygiene. For this reason, such authentication system is used for onlysome limited users who require very high security. Recently, anon-contact authentication system which authenticates the user bysensing an image of the user's eye using a camera is available. However,in case of such non-contact system, since the image sensing condition ofthe user by the camera is unstable, sufficiently high authenticationprecision cannot be assured.

In a system that uses user's fingerprint information, the user touches areader with his or her finger to sense its fingerprint, and can beauthenticated by matching feature points. This system is unsusceptibleto physical growth and aging as in the iris pattern. However, since theuser's skin touches the contact surface of a detection device with hisor her finger, the contact surface is contaminated with fat and sweat ofthe hand, and the precision deteriorates during use. Since the usersdirectly touch the detection surface with fingers, some users may hateto use such system in terms of hygiene. If the hand of a person to beauthenticated is dry, his or her finger cannot well contact thedetection surface, and a fingerprint cannot be satisfactorily read.

In a personal authentication system using user's voice/utteranceinformation, the authentication precision depends on user's physicalconditions. For example, even the same person may often have lower voicereproducibility (e.g., a person may have a hoarse voice due to cold orhangover). For this reason, speaker recognition has a problem with itsauthentication precision, and has not been developed to a practicallevel.

In a personal authentication system that uses user's facial information,the user need not directly physically touch an authentication apparatus,and the user's facial image which is sensed by a camera need only beanalyzed to authenticate that user. Therefore, compared to othersystems, the load on the user can be lightened, and such system can berelatively easily used to open/close a gate. Such personalauthentication system using user's facial information is described in,e.g., Jpn. Pat. KOKAI Publication Nos. 9-251534 and 11-175718.

In order to improve the authentication precision of the authenticationsystem that utilizes a facial image, a facial image with a largeinformation size must be sensed, and pixels equal to or larger than apredetermined value in number are required. However, when the height ofthe user is relatively higher than the camera position for image sensingor when the standing position of the user is far from the camera, afacial image to be sensed is small, the number of pixels of the facialimage is also small and, hence, a given image information size cannot beassured, thus impairing the recognition precision. If the standingposition of the user or the illumination condition of the image sensingsite is different from that upon registration, i.e., the image sensingconditions between registration and authentication are largelydifferent, the obtained image information varies, and personalauthentication consequently fails.

If the user creates another facial expression upon sensing a facialimage, the obtained facial pattern changes. Therefore, in order toimprove the precision of personal authentication, various facialexpressions must be registered upon registering a dictionary of a givenuser. Upon registering various facial expressions, if the user isstrained, his or her expression looks stern. As a result, expectedfacial expressions cannot be registered, and a facial expression uponauthentication becomes largely different from that upon registration,thus disturbing improvement in recognition precision. Conversely, if thesystem asks for user's cooperation to sense various facial expressionsupon registering a dictionary, some users overreact, and a facialexpression upon overreaction becomes largely different from that uponauthentication.

BRIEF SUMMARY OF THE INVENTION

It is an object of the present invention to provide a personalauthentication apparatus and personal authentication method, which canimprove the authentication precision by reducing the load on the user.

According to the first aspect of the present invention, a personalauthentication apparatus comprises: facial region extraction unitconfigured to extract an image of a facial region of a person obtainedfrom image sensing input unit; guide unit configured to guide motion ofthe person of interest; feature amount extraction unit configured toextract a feature amount of a face from the image of the facial regionextracted by the facial region extraction unit while the motion isguided by the guide unit; dictionary registration unit configured toregister the feature amount extracted by the feature amount extractionunit as a feature amount of the person of interest; and a unitconfigured to authenticate the person of interest in accordance with asimilarity between the feature amount extracted by the feature amountextraction unit, and a feature amount registered by the dictionaryregistration unit.

According to the second aspect of the present invention, a personalauthentication method comprises: extracting an image of a facial regionof a person obtained from image sensing input means; guiding motion ofthe person of interest; extracting a feature amount of a face from theextracted facial region while the motion is guided; and authenticatingthe person of interest in accordance with a similarity between theextracted feature amount extracted by the feature amount extractionmeans, and a feature amount of the person of interest which isregistered in advance.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

FIG. 1 is a schematic diagram of the first embodiment of the presentinvention;

FIGS. 2A through 2D are explanatory views of facial region extraction inthe first embodiment;

FIG. 3 is an explanatory view of a normalized pattern and feature vectorin the first embodiment;

FIG. 4 is a recognition flow chart in the first embodiment;

FIG. 5 is an explanatory view of a similarity in the first embodiment;

FIGS. 6A through 6C show an example of an interface upon registration inthe first embodiment;

FIGS. 7A through 7C show an example of an interface upon authenticationin the first embodiment;

FIGS. 8A and 8B show another example of an interface upon registrationin the first embodiment;

FIGS. 9A and 9B show another example of an interface upon authenticationin the first embodiment;

FIGS. 10A through 10E show an example of an interface upon registrationin the second embodiment;

FIGS. 11A through 11E show an example of an interface uponauthentication in the second embodiment;

FIGS. 12A through 12E show another example of an interface uponauthentication in the second embodiment; and

FIG. 13 is a flow chart showing the process of an image sensingcondition extraction means and guide means in the first and secondembodiments.

DETAILED DESCRIPTION OF THE INVENTION

Preferred embodiments of the present invention will be describedhereinafter with reference to the accompanying drawings.

The first embodiment of the present invention will be described first.

FIG. 1 shows a schematic arrangement of the first embodiment. An imagesensing input unit 1 inputs a facial image of a user (person to beauthenticated) upon registration and authentication, and comprises a CCDcamera used to acquire a moving image, still image, or the like,lighting equipment used to light up an image sensing space of the user,and the like. An analog image signal sensed by a CCD or CMOS camera isconverted into a digital signal by an analog/digital conversion unitsuch as an image input board, and the digital image signal is stored inan image memory. The image memory may be mounted on the image inputboard, or may use an internal memory or external storage device of acomputer corresponding to an information management unit 9.

A facial region extraction unit 2 detects a facial image region or headimage region from an image of the person to be authenticated, which isstored in the image memory. There are some facial region extractionmethods. For example, when a sensed image is a color image, a methodusing color information is available. More specifically, the sensedcolor image is converted from an RGB color space which is specified bythree components Red, Green, and Blue into an HSV color space whichspecified by three components Hue (color appearance, hue), Saturation(saturation), and Value (lightness). The converted image is segmented byregion segmentation into a facial image region, head hair region, andthe like using color information such as hue, saturation, and the like.Then, a facial region is detected from the segmented partial regionsusing a region growing method or the like. In the region growing method,a target figure (region) is extracted by combining pixels having similarnatures around an appropriately designated pixel (start pixel) in turn(or by expanding a region of that region to surrounding pixels). Detailsof the region growing method are described in, e.g., Junichiro Toriwaki“Three-dimensional Digital Image Processing”, Jul. 5, 2002, Shokodo.

As another method of obtaining a facial region, a template for facialdetection, which is prepared in advance, is moved in an image tocalculate correlation values at respective positions. A region with thehighest correlation value is determined to be a region with a highcoincidence with the template, i.e., a facial region in the image. Instill another method, distances or similarities may be calculated by anEigenface method or subspace method in place of the correlation valuesto extract a region with the minimum distance or maximum similarity. Inyet another method, near infrared light may be projected in addition tothe CCD camera and a region corresponding to a face is extracted basedon the reflected light. The present invention can adopt any of theaforementioned method or other methods.

A facial component detection unit 3 detects facial components such aseyes, a nose, a mouth, and the like from the image of the facial region.For example, the eye positions are detected from the image of the facialregion extracted by the facial region extraction unit 2. As thedetection method, a method based on pattern matching as in the aboveextraction method, a method described in a reference (Kazuhiro Fukui &Osamu Yamaguchi, “Facial Feature Point Extraction by Combination ofShape Extraction and Pattern Matching”, IEICE Journal, Vol. J80-D-II,No. 8, pp. 2170-2177 (1997)), and the like may be used. In thisembodiment, any of the aforementioned method or other methods may beused.

A feature amount extraction unit 4 extracts an image feature amountrequired for personal authentication from an input image. Based on theposition of the facial region detected by the facial region extractionunit 2 and those of the facial components detected by the facialcomponent detection unit 3, a region having a given size and shape isclipped. Density information of the clipped image is used as featureinformation. At least two components are selected from the facialcomponents detected by the facial component detection unit 3. If a linesegment that connects these two components falls within the range of thefacial region extracted in advance at a given ratio, it is convertedinto an m (pixels)×n (pixels) region (m and n are integers equal to orlarger than 1), which is used as a normalized pattern.

FIGS. 2A through 2D show an extraction example when the two eyes areselected as facial components in the facial region extraction method ofthe personal authentication apparatus. In FIG. 2A, a black rectanglewhich indicates the position of the facial region extracted by thefacial region extraction means 2 is superimposed on the facial image ofa person to be authenticated, which is sensed by the image sensing inputmeans 1, and black cross lines indicating the positions of the facialcomponents (eyes, nasal cavities, and mouth edges) extracted by thefacial component detection unit 3 are further superimposed. FIG. 2Billustrates an image of the facial image. On such image of the facialregion, let V1 be a vector which connects from the right eye to the lefteye, and has a value corresponding to the distance from the right eye tothe left eye, C be the central point of that vector, and V2 be a vectorwhich is headed from C to the middle point between the two nasalcavities, as shown in FIG. 2C. If the distances from central point C ofvector V1 to the respective components have a given ratio, (e.g., theratio between the sizes of V1 and V2 falls within a predeterminedrange), it is determined that the region is a facial region whichincludes the two eyes and nasal cavities. Density pixel information isgenerated from that facial image, thus obtaining density pixel matrixinformation of m pixels×n pixels, as shown in FIG. 2D. The density pixelmatrix information pattern shown in FIG. 2D will be referred to as anormalized pattern hereinafter.

In this normalized pattern, the density values of elements (pixels) ofan m (pixels)×n (pixels) matrix line up, as shown in the left figure ofFIG. 3. When such matrix is converted into vector expression, the matrixis expressed by an (m×n)-dimensional vector, as shown in the rightfigure of FIG. 3. This feature vector Nk (k indicates the number ofnormalized patterns obtained for an identical person) is used in thesubsequent processes.

A feature amount used in person recognition is a subspace obtained bylowering the number of data dimensions of an orthonormal vector, whichis obtained by calculating a correlation matrix of feature vector Nk andthen calculating an K-L expansion of that matrix. Note that correlationmatrix C is given by:

$C = {\frac{1}{r}{\sum\limits_{k = 1}^{r}{N_{k}N_{k}^{T}}}}$

where r is the number of normalized patterns acquired for an identicalperson. By diagonalizing C, principal components (eigenvectors) areobtained. M out of these eigenvectors in descending order of eigenvalueare used as a subspace. This subspace is used as a personalauthentication dictionary.

Referring back to FIG. 1, a dictionary registration unit 5 registers thefeature amount extracted by the feature amount extraction unit 4together with index information such as the ID number of the person ofinterest, spatial space (eigenvalues, eigenvectors, the number ofdimensions, the number of sample data), and the like.

An authentication unit 6 compares the feature amount registered in thisdictionary and that extracted from the sensed facial image, and collatestheir similarity. FIG. 4 is a flow chart showing that process. When aperson to be authenticated appears in front of the personalauthentication apparatus of the present invention, an authenticationprocedure starts (step S1), and an image of the person to beauthenticated is sensed and input to the authentication apparatus (stepS2). A facial region is extracted from the input image by theaforementioned method (step S3), and an image feature amount requiredfor personal authentication is extracted from the extracted facialregion of the input image (step S4). In this way, an authentication dataacquisition process is repeated (steps S5 and S6) until a predeterminednumber of (n) normalized patterns suited to verification are obtained.After the predetermined number of (n) normalized patterns of the personto be authenticated are obtained, pattern matching is made with adictionary facial image of the person to be authenticated, which isregistered in advance, by a mutual subspace method (step S7). If apredetermined similarity is obtained, the person to be authenticated isidentified to be the person he or she claims to be; otherwise, theperson to be authenticated is identified not to be the person he or sheclaims to be.

Note that the similarity is defined by distances and vector angles makein an M-dimensional subspace specified by a feature amount, as shown inFIG. 5. In FIG. 5, assume that data of person A having a feature amountexpressed by “pattern 1” and that of person B having a feature amountexpressed by “pattern 2” are registered in an (N×N)-dimensional space.Data of a person to be authenticated (a vector indicated by a black boldline in FIG. 5) is input. The differences (distances) between a vectorindicating the data of the person to be authenticated and thoseexpressed by patterns 1 and 2, and the like are calculated. Let len1 bethe distance between the vector which indicates the data of the personto be authenticated, and that expressed by pattern 1, len2 be thedistance between the vector which indicates the data of the person to beauthenticated, and that expressed by pattern 2, θ1 be the angle thevector which indicates the data of the person to be authenticated makeswith the vector expressed by pattern 1, and θ2 be the angle the vectorindicating data of the person to be authenticated makes with the vectorexpressed by pattern 2. As can be seen from FIG. 5, since len1 issmaller than len2, and θ1 is smaller than θ2, a similarity between theperson to be authenticated and person A is larger than that between theperson to be authenticated and person B. In this manner, upon comparingthe feature amount of the person to be authenticated with those ofpersons A and B, it is determined that the feature vector of the alreadyregistered person (person A and B) which has a smaller distance from andmakes a smaller angle with that of the person to be authenticated has ahigher similarity to that person, and that person is identical to theperson to be authenticated, thus outputting a verification result.

When the facial image of a person to be authenticated is registered in adictionary, the person to be authenticated normally inputs his or her IDnumber and stands at a position relatively near the image sensing inputunit 1 to sense his or her face and to register the sensed image. Bycontrast, upon personal authentication, if the need for inputting the IDnumber is obviated, the person to be authenticated may undergo anauthentication process at a position which is not so near the personalauthentication apparatus. When the image sensing conditions of theperson to be authenticated are largely different upon image registrationand authentication, the feature amount of a face used by theauthentication unit 6 becomes considerably different from that used inthe dictionary registration unit 5 even for an identical person, and theperson cannot often be recognized as a person he or she claims to be.

That is, when the standing position of the person to be authenticatedupon registration is largely different from that upon authentication,the size of a person to be sensed and that of a facial region of theperson contained in the sensed image are different. More specifically,an image sensed near the image sensing means upon registration includesa relatively small facial region. To prevent this, the size of theextracted facial region can be controlled to fall within a given range.

Also, the irradiation condition of light coming through a window largelyvaries depending on the hours (e.g., morning, daytime, evening, and thelike) of the day. Also, outside light coming from the window alsolargely change depending on seasons. If outside light is too strong, afacial image sensed under such condition blurs by halation, and a facialregion cannot be clipped from such image. To prevent this problem, theaverage luminance value of the extracted facial image can be controlledto fall within a given range.

In order to solve the aforementioned problems, it is effective to add animage sensing condition extraction unit 8 and guide unit 7. The imagesensing condition extraction unit 8 extracts image sensing conditionswhich include standing positions upon registration and authenticationand the like, and has a function of checking if the size and the averageluminance value of the facial region extracted by the facial regionextraction unit 2 fall within predetermined ranges. The guide unit 7guides the person to be authenticated in accordance with the extractedimage sensing conditions, so as to attain the same image sensingconditions upon dictionary registration and authentication.

FIGS. 6A through 6C show an example of an interface used uponregistering a facial image of a person to be authenticated in adictionary when the person to be authenticated undergoes personalauthentication while he or she stands near the personal authenticationapparatus which is equipped in front of him or her. When the person tobe authenticated stands near the personal authentication apparatus, asshown in FIG. 6A, the image of this person is displayed on a monitor,and the image sensing condition extraction means 8 calculates the sizeof a facial region to be extracted from the personal image input fromthe image input means and the average luminance value of pixels includedin the facial region. When the size of the facial region to be extractedbecomes larger than a predetermined size, or when the average luminancevalue of pixels becomes larger than a predetermined threshold value, itis determined that the person to be authenticated falls within an imagesensing range. Then, as shown in FIG. 6B, an elliptic frame issuperimposed near the facial region, and a bleep tone is generated toinform the person to be authenticated of the start of registration. Inthis case, the ID number and the like required to register this personare input prior to registration using a number input unit such as aten-key pad and the like. Note that messages such as “registrationstart” and the like for the person to be authenticated are displayed onan upper portion of the screen, so that the person to be authenticatedcan look up not to hide his or her forehead with hair upon sensing afacial image (see FIGS. 6B and 6C).

After a predetermined number of images required for dictionaryregistration are acquired, bleep tones that inform the person of the endof registration are produced, and a message that advises accordingly isdisplayed, as shown in FIG. 6C. At that time, normalized patterns areextracted from the predetermined number of input images, anN-dimensional feature vector is generated, and a subspace is calculatedand is registered in the dictionary by the dictionary registration unit5.

Upon authenticating a person, as shown in FIGS. 7A through 7C, theperson to be authenticated proceeds to an authentication procedure whilethe image sensing condition extraction unit 8 monitors the facial imageacquisition condition of the person. As shown in FIG. 7A, when theperson to be authenticated approaches the personal authenticationapparatus, the facial image acquisition condition of the person to beauthenticated is monitored (e.g., the size of the facial region and theaverage luminance value of pixels are checked) by the same operation asthat upon registration, and it is checked if the conditions such as theposition, posture, and the like of the person to be authenticated matchthose for image sensing. The personal authentication procedure does notstart before the person to be authenticated reaches a facial imagesensing position. When the person to be authenticated has reached thefacial image sensing position, a bleep tone is generated, and anelliptic frame is superimposed on the facial image of the person to beauthenticated displayed on the monitor screen together with a message“authentication starts”, thus starting the authentication procedure.After a predetermined number of authentication images are acquired,bleep tones are generated to inform the person of the end of theauthentication procedure, and a message of the authentication result isdisplayed on the monitor screen.

FIG. 13 is a flow chart showing the aforementioned dictionaryregistration process and personal authentication procedure. A facialregion is extracted (step S12) from an input personal image of theperson to be authenticated (step S11) using color information, atemplate, or the like. Upon registration, an image of a facial imagewith an image size equal to or larger than a predetermined size isextracted (step S13). If the average luminance value of the image of thefacial region is equal to or larger than a predetermined value (stepS14), a normalized pattern of the person to be authenticated is acquireduntil a predetermined number of normalized patterns are acquired. Afterthat, the personal authentication procedure is completed by determininga similarity between the acquired normalized patterns and the alreadyregistered normalized patterns (step S20).

In the aforementioned registration/authentication procedure, when theperson to be authenticated moves away from the image sensing apparatusor falls outside the image sensing range by loosing his or her balanceafter the registration/authentication procedure has started, imageacquisition is canceled. In this case, a normalized pattern forregistration or authentication is not calculated. After that, when theperson to be authenticated meets the facial image acquisition conditionsagain, and is ready to acquire an image of the facial region, theregistration/authentication process is repeated until a predeterminednumber of normalized patterns are generated.

In the above embodiment, since the image sensing means is set to locatethe face of the person to be authenticated at nearly the center of theacquired image, the person to be authenticated is located in front ofthe personal authentication apparatus and approaches it. However, whenthe image sensing unit of the personal authentication apparatus is seton a wall in the neighborhood of an entrance, a facial image is acquiredwhile the person to be authenticated obliquely looks in the imagesensing unit. Hence, the standing position of the person to beauthenticated may deviate not only in a direction to and from the imagesensing device but also in the right-and-left directions. FIGS. 8A and8B and FIGS. 9A and 9B show a case wherein a normalized pattern can beextracted only when the facial image is located at the central positionof the acquired image, so as to match the image sensing conditions ofthe person to be authenticated in such environment.

In FIG. 8A, when the facial image of the person to be authenticated isdisplayed on the monitor screen, a bleep tone is generated to inform theperson of the start of the registration procedure, and a message thatadvises accordingly is displayed on the monitor. In addition, the facialimage of the person to be authenticated, which is sensed by the imagesensing unit is displayed on the monitor, and a message and cross markwhich guide the position and posture of the person to be authenticatedto locate the facial image at the center of the screen are displayed.When the facial image of the person to be authenticated is captured atthe center of the screen, acquisition of the facial image, extraction ofa feature amount, and registration of an authentication image start.After a predetermined number of data are acquired, bleep tones aregenerated, and a message that informs the person of the end ofregistration is displayed at the same time (see FIG. 8B).

Upon authenticating a person, as in registration, when the person to beauthenticated approaches the personal authentication apparatus, theposition and posture of the person to be authenticated are guided sothat the facial image of the person to be authenticated is located atthe center of the sensed image (see FIG. 9A). When the facial image ofthe person to be authenticated is captured at the center of the screen,an authentication image is acquired, and the authentication procedurestarts. After a similarity with registered data is determined, anaudible message is generated, and the authentication result isdisplayed, thus ending the authentication procedure (see FIG. 9B).

The second embodiment of the present invention will be described below.

In the first embodiment, the facial image of the person to beauthenticated, which is sensed upon dictionary registration or personalauthentication, is displayed on the monitor, and the person to beauthenticated is guided based on the displayed contents. However, manyusers may be strained when their facial images are displayed on themonitor in practice. Especially, since many users are strained upondictionary registration, the facial expression upon personalauthentication becomes different from that upon dictionary registration,and authentication often fails. Also, when the facial expression changeslargely, since the mouth and eye positions apparently change, thefeature vector changes, and authentication often fails. On the otherhand, a shadow is often cast on a face due to the influences of hairstyle of the person to be authenticated and illumination, and the pixelvalues of the obtained image change largely due to the influence ofillumination and shadow, thus impairing the authentication precision.

In order to solve such problems, by registering the facial image whilemoving the face of the person to be authenticated upon registration andauthentication, the authentication precision can be improved. The secondembodiment is an invention which is made to solve the above problems.More specifically, the guide unit 7 displays a character on the monitorin place of the facial image of the person to be authenticated, therebyguiding the person to be authenticated.

FIGS. 10A through 10E are views for explaining the guide sequence of theguide unit 7 upon dictionary registration. In FIG. 10A, when thedictionary registration procedure starts together with generation of ableep tone, a message and character used to guide the motion of the faceof the person to be authenticated are displayed on the monitor togetherwith a message that indicates the start of registration. Morespecifically, the character is displayed to make a round clockwise alongthe circumference of the display region of the monitor. The person to beauthenticated moves his or her face to follow the movement of thecharacter (FIGS. 10B through 10D). During this interval, the personalauthentication apparatus senses different facial images of the person tobe authenticated, who looks up, down, and right, and left, extractsfeature amounts, and generates normalized patterns. Upon completion ofgeneration of a predetermined number of normalized patterns, which areto be registered in a dictionary, a message “end of registration” and acharacter are displayed, thus ending the registration procedure.

In this embodiment, the image sensing condition extraction unit 8calculates an image sensing range on the basis of the size and theaverage luminance value of the facial region as in the first embodiment.That is, when the person to be authenticated approaches the imagesensing range, the image sensing range is calculated. If it isdetermined that a facial image can be sensed, a character created bycomputer graphics (CG) or the like is displayed on the monitor in placeof the facial image of the person and the elliptic frame. The charactermay move about in the screen until n normalized patterns are acquired inplace of making a round along the circumference of the screen. In thiscase, when the apparatus guides the person to follow the motion of thecharacter by moving not only eyes but also the face, facial images freefrom any nonuniformity against a change in illumination can be acquired.Furthermore, when a bowing character is displayed upon completion of theregistration procedure, it can relax the person to be authenticated, andfacial image data of the person to be authenticated can be acquired in arelatively relaxed state.

FIGS. 11A through 11E are views for explaining the guide procedure ofthe guide unit upon personal authentication. The basic procedure is thesame as that upon dictionary registration. In FIG. 11A, when a personalauthentication procedure starts, a character makes a round along thecircumference of the monitor to guide the movement of the face of theperson to be authenticated (FIGS. 11B through 11D). After apredetermined number of normalized patterns are acquired and anauthentication result is obtained, a message “end of authentication” anda character are displayed (FIG. 11E).

Upon completion of personal authentication, the number of times theperson to be authenticated has passed the door may be presented, thusproviding information that attracts the interest of the person to beauthenticated. When the information that attracts the interest of theperson to be authenticated is presented, the face of the person to beauthenticated can be closer to the authentication apparatus, therebyfurther improving the authentication precision. Alternatively, as shownin FIGS. 12A through 12E, a plurality of different characters to berandomly displayed may be prepared, and are used daily or randomly, thusattracting the interest of the person to be authenticated. Also, asshown in FIG. 12E, fortune-telling using a similarity uponauthentication (a better fortune-telling result can be obtained withincreasing similarity) may be displayed to attract the interest of theperson to be authenticated. With this arrangement, since the person tobe authenticated stands at a position near the authentication apparatusand approaches his or her face to the monitor screen to look into it,the image sensing conditions upon registration and authentication canbecome stable, and a predetermined number of normalized patterns can beacquired easily, thus improving the authentication precision.

Additional advantages and modifications will readily occur to thoseskilled in the art. Therefore, the invention in its broader aspects isnot limited to the specific details and representative embodiments shownand described herein. Accordingly, various modifications may be madewithout departing from the spirit or scope of the general inventiveconcept as defined by the appended claims and their equivalents.

1. A personal authentication apparatus comprising: an image sensinginput unit configured to sense a person and input a first image atregistration and a second image at aunthentication; a facial regionextraction unit configured to extract first and second facial imagesfrom the first and second images input by the image sensing input unit;a guide unit configured to display a guidance of an image sensingcondition of the person at registration; a feature amount extractionunit configured to extract first and second feature amounts of the firstand second facial images; a dictionary registration unit configured toregister the first feature amount; and an authenticating unit configuredto perform authentication by determining a similarity between the firstfeature amount registered by the dictionary registration unit and thesecond feature amount.
 2. The apparatus according to claim 1, furthercomprising: an image sensing condition extraction unit configured toextract an image sensing condition of the person at registration on thebasis of a size or luminance of the first facial image, and wherein theguide unit displays the guidance so that the image sensing conditionextracted by the image sensing condition extraction unit falls within apredetermined value range.
 3. The apparatus according to claim 1,wherein the guide unit displays a character which relaxes the person andguides a movement of the person.
 4. The apparatus according to claim 1,wherein the guide unit displays the first facial image and a guide markto which the person is to be moved.
 5. A personal authentication methodcomprising: sensing a person and inputting a first image at registrationand a second image at authentication; extracting first and second facialimages from the first and second images input by the inputting;displaying a guidance of an image sensing condition of the person atregistration; extracting first and second feature amounts of the firstand second facial images; registering the first feature amount; andperforming authentication by determining a similarity between the firstfeature amount registered by the registering and the second featureamount.
 6. The method according to claim 5, further comprising:extracting an image sensing condition of the person at registration onthe basis of a size or luminance of the first facial image, anddisplaying the guidance so that the image sensing condition extracted bythe extracting falls within a predetermined value range.
 7. The methodaccording to claim 5, further comprising: displaying a character whichrelaxes the person and guides a movement of the person.
 8. The methodaccording to claim 5, further comprising: displaying the first facialimage and a guide mark to which the person is to be moved.